Lecture
Information Theory and Coding
Related lectures (39)
Information Theory: Source Coding, Cryptography, Channel Coding
Covers source coding, cryptography, and channel coding in communication systems, exploring entropy, codes, error channels, and future related courses.
Random Coding: Achievability and Proof Variants
Explores random coding achievability and proof variants in information theory, emphasizing achievable rates and architectural principles.
Lecture: Shannon
Covers the basics of information theory, focusing on Shannon's setting and channel transmission.
Information Theory: Entropy and Information Processing
Explores entropy in information theory and its role in data processing and probability distributions.
Information Theory: Source Coding
Covers source coding, typical sequences, stationarity, and efficient encoding in information theory.
Information Measures: Entropy and Information Theory
Explains how entropy measures uncertainty in a system based on possible outcomes.
Binary Coding: Channel Decoding
Explores binary channel decoding and vector spaces in coding theory.
Error Correction Codes: Theory and Applications
Covers error correction codes theory and applications, emphasizing the importance of minimizing distance for reliable communication.
Mutual Information and Entropy
Explores mutual information and entropy calculation between random variables.
Information Theory: Source Coding & Channel Coding
Covers the fundamentals of information theory, focusing on source coding and channel coding.